Tkacik Group

Information Processing in Biological Systems

How do networks built out of biological components – neurons, signaling molecules, genes, or even cooperating organisms – process information? In contrast to engineered systems, biological networks operate under strong constraints due to noise, limited energy, or specificity, yet nevertheless perform their functions reliably. The group uses biophysics and information theory to understand the principles and mechanisms behind this remarkable phenomenon.

How can cells in a multicellular organism reproducibly decide what tissue they are going to become? How do neurons in the retina cooperate to best encode visual information into neural spikes? How does the physics at the microscopic scale, which dictates how individual regulatory molecules interact with each other, constrain the kinds of regulatory networks that are observed in real organisms today, and how can such networks evolve? These are some of the questions addressed by the Tkačik group. About half of their time is dedicated to data-driven projects performed in close collaboration with experimentalists, and half on purely theoretical projects. Their goal is to develop theoretical ideas about biological network function and connect them to high-precision data.


On this site:


Team

Image of Reka Borbely

Reka Borbely

PhD Student

Image of Athina Diakogianni

Athina Diakogianni

PhD Student


Image of Mantas Gabrielaitis

Mantas Gabrielaitis

Postdoc

Image of Michal Hledik

Michal Hledik

PhD Student

Image of Fabrizio Lombardi

Fabrizio Lombardi

Postdoc


Image of Ekaterina Maksimova

Ekaterina Maksimova

PhD Student

Image of Wiktor Mlynarski

Wiktor Mlynarski

Postdoc

Image of Simon Rella

Simon Rella

PhD Student


Image of Natalia Ruzickova

Natalia Ruzickova

PhD Student

Image of Sreyam Sengupta

Sreyam Sengupta

PhD Student


Current Projects

Visual encoding in the retina | Genetic regulation during early embryogenesis | Collective dynamics | Evolution of gene regulation


Publications

Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE. 2022. Inferring couplings in networks across order-disorder phase transitions. Physical Review Research. 4(2), 023240. View

Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543. View

Zisis T, Brückner D, Brandstätter T, Siow WX, d’Alessandro J, Vollmar AM, Broedersz CP, Zahler S. 2022. Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration. Biophysical Journal. 121(1), P44-60. View

Bodova K, Szep E, Barton NH. 2021. Dynamic maximum entropy provides accurate approximation of structured population dynamics. PLoS Computational Biology. 17(12), e1009661. View

Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning for studying cellular processes under spatiotemporal control. ACS Applied Materials and Interfaces. 13(30), 35545–35560. View

View All Publications

ReX-Link: Gasper Tkacik


Career

since 2017 Professor, Institute of Science and Technology Austria (ISTA)
2011 – 2016 Assistant Professor, Institute of Science and Technology Austria (ISTA)
2008 – 2010 Postdoc, University of Pennsylvania, Philadelphia, USA
2007 Postdoc, Princeton University, USA
2007 PhD, Princeton University, USA


Selected Distinctions

2018 HFSP Grant
2012 HFSP Grant
2003 Burroughs-Wellcome Fellowship, Princeton University
2002 Golden Sign of the University of Ljubljana


Additional Information

Open Tkacik group website
Physics & Beyond at ISTA



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